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Query and modify live Power BI Desktop models through its in-memory engine.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-powerbi-desktop" yet — see the docs or source repo.
Connect to the currently open Power BI Desktop instance, list all tables, columns, measures, and relationships, and summarize the model structure in English.
A list of core model objects and a brief explanation of the data model structure.
Create a new measure named 'Gross Margin Rate' in the Sales table with the formula DIVIDE([Gross Profit],[Total Sales]), and validate whether the formula works.
The measure is created, with confirmation on whether it was added successfully and whether any syntax or dependency issues exist.
Scan the current Power BI data model for unused columns, potentially duplicate measure names, and relationship issues, then provide optimization suggestions.
An audit report listing detected issues and actionable optimization recommendations.
Connect to Power BI via MCP to inspect models and analyze data.
Connect to Power BI with natural language to query and refresh data.
Discover and connect Power BI workspaces and semantic models for data access.
Enable AI agents to create and manage Power BI semantic models.
Access financial data and analysis tools for faster research and modeling.
Edit Power BI project reports locally in PBIR format for faster maintenance.